Privacy And Data Protection Challenges in The Era of Artificial Intelligence

Artificial intelligence (AI) structures rely on large amounts of private records for training and deployment. This creates privacy concerns that common fact safety systems now would not have been designed to handle, along with opaque statistical series, net scraping without meaningful consent, inferences about sensitive features, leakage of training statistics from models, surveillance, and automated decision making. The rapid development of generative AI has heightened those concerns, as fashions that are proficient on internet-scale data currently are used by tens of millions of those who mechanically embed private records into them. It assesses the main legal frameworks, particularly the EU General Data Protection Regulation (GDPR), the EU AI Act, and India’s Digital Personal Information Protection Act, 2023, and identifies gaps in how they handle inferred facts, educated fashions, and enforcement of erasure rights. It also considers regulatory enforcement enjoy, consisting of actions against Clearview AI and ChatGPT, to show how current regulation is applied to AI in practice. Finally, it evaluates technical security measures consisting of differential privacy and connected knowing, along with organizational measures consisting of privacy-by-design, impact assessments, and independent audits. The paper argues that effective security requires the implementation of legal responsibilities mixed with privacy-preserving engineering, instead of either on my own, and that responsibility should be shifted upstream to people who design, train, and deploy AI systems. It concludes with suggestions for regulators, with special reference to the Indian context.